Related publications about Open Science

For reference we include links to important prior and related work done by research groups which are using open data from the HEP community.

Physics results obtained using Open Data

• Search for dark matter production in association with the Z'boson at the LHC in pp collisions at = 8 TeV using Monte Carlo simulations, S. Elgammal, M. Louka, A. Ellithi and M. Hussein, Chin.Phys.C 45 083001 (2021) (07 Mar 2021).
• Analysis of Prospective Super-Symmetry Inherent in the pp Collision Data at 7 TeV from CMS Collaboration Using Novel Two-Dimensional Multifractal-Detrended Fluctuation Analysis Method with Rectangular Scale, S. Bhaduri and A. Bhaduri, arXiv 2012.00442 (01 Dec 2020) [1 citation].
• Probing resonance states in high-energy interaction: a novel approach using complex network technique based on symmetry scaling, S. Bhaduri, A. Bhaduri and D. Ghosh, Eur.Phys.J.A 56 244 (2020) (30 Sep 2020) [1 citation].
• Searching for Supersymmetry at LHC Using the Complex-Network-Based Method of the Three-Dimensional Visibility-Graph, S. Bhaduri and A. Bhaduri, MDPI Physics 2 (2020) (10 Sep 2020).
• Lorentz and permutation invariants of particles III: Constraining nonstandard sources of parity violation, C. Lester, W. Haddadin and B. Gripaios, Int.J.Mod.Phys.A 37 2250093 (2022) (12 Aug 2020) [5 citations].
• The Hidden Geometry of Particle Collisions, P. Komiske, E. Metodiev and J. Thaler, JHEP 07 006 (2020) (21 Apr 2020) [54 citations]. Uses CMS Open Data
• Reinterpretation of LHC Results for New Physics: Status and Recommendations after Run 2, W. Abdallah et. al., SciPost Phys. 9 022 (2020) (19 Mar 2020) [84 citations].
• Dataset of tau neutrino interactions recorded by the OPERA experiment, G. De Lellis, S. Dmitrievsky, G. Galati, A. Lavasa, T. Šimko, I. Tsanaktsidis and A. Ustyuzhanin, EPJ Web Conf. 245 08013 (2020) (01 Jan 2020) [1 citation].
• Study of Di-muon Production Process in pp Collision in CMS Data from Symmetry Scaling Perspective, S. Bhaduri, A. Bhaduri and D. Ghosh, Adv.High Energy Phys. 2020 4510897 (2020) (22 Nov 2019) [7 citations].
• Exploring the Space of Jets with CMS Open Data, P. Komiske, R. Mastandrea, E. Metodiev, P. Naik and J. Thaler, Phys.Rev.D 101 034009 (2020) (22 Aug 2019) [52 citations].
• Testing non-standard sources of parity violation in jets at the LHC, trialled with CMS Open Data, C. Lester and M. Schott, JHEP 12 120 (2019) (25 Apr 2019) [18 citations].
• Searching in CMS Open Data for Dimuon Resonances with Substantial Transverse Momentum, C. Cesarotti, Y. Soreq, M. Strassler, J. Thaler and W. Xue, Phys.Rev.D 100 015021 (2019) (11 Feb 2019) [17 citations].
• Symmetry-Scaling Based Complex Network Approach to Explore Exotic Hadronic States in High-Energy Collision, S. Bhaduri, A. Bhaduri and D. Ghosh, Phys.Part.Nucl.Lett. 16 (2019) (16 Jan 2019) [4 citations].
• Searching for rare charm decays, performing alignment studies and improving the analysis ecosystem in HEP, C. Burr, C. Parkes and M. Gersabeck, Unknown (01 Jan 2019).
• Intermittency in pseudorapidity space of pp collisions at = 7 TeV, Z. Ong, E. Yuen, H. Ang, A. Chan and C. Oh, EPJ Web Conf. 206 09004 (2019) (01 Jan 2019) [3 citations].
• Factorization of two-particle distributions measured in Pb-Pb collisions at \sqrt {s_{NN}} = 5.02 TeV with the ALICE detector, C. Bourjau and J. Gaardhøje, Unknown (01 Jan 2018).
• Exposing the QCD Splitting Function with CMS Open Data, A. Larkoski, S. Marzani, J. Thaler, A. Tripathee and W. Xue, Phys.Rev.Lett. 119 132003 (2017) (17 Apr 2017) [68 citations].

Use of Open Data to support software, machine learning and algorithms development

• Analysis-Specific Fast Simulation at the LHC with Deep Learning, C. Chen, O. Cerri, T. Nguyen, J. Vlimant and M. Pierini, Comput.Softw.Big Sci. 5 15 (2021) (09 Jun 2021) [18 citations].
• Evaluating Query Languages and Systems for High-Energy Physics Data [Extended Version], D. Graur, I. Müller, M. Proffitt, G. Fourny, G. Watts and G. Alonso, arXiv 2104.12615 (26 Apr 2021) [5 citations]. Uses CMS Open Data
• End-to-end jet classification of boosted top quarks with the CMS open data, M. Andrews et. al., EPJ Web Conf. 251 04030 (2021) (19 Apr 2021) [15 citations].
• Porting CMS Heterogeneous Pixel Reconstruction to Kokkos, M. Kortelainen, M. Kwok, T. Childers, A. Strelchenko and Y. Wang, EPJ Web Conf. 251 03034 (2021) (14 Apr 2021) [5 citations]. Uses CMS Open Data
• Data Analysis with GPU-Accelerated Kernels, J. Pata, I. Dutta, N. Lu, J. Vlimant, H. Newman, M. Spiropulu, C. Reissel and D. Ruini, PoS ICHEP2020 908 (2021) (02 Mar 2021) [2 citations]. Uses ATLAS and CMS Open Data
• Performance of CUDA Unified Memory in CMS Heterogeneous Pixel Reconstruction, M. Kortelainen and M. Kwok, EPJ Web Conf. 251 03035 (2021) (25 Feb 2021). Uses CMS Open Data
• Machine Learning scientific competitions and datasets, D. Rousseau and A. Ustyuzhanin, arXiv 2012.08520 (15 Dec 2020) [3 citations].
• Quantum-inspired machine learning on high-energy physics data, T. Felser, M. Trenti, L. Sestini, A. Gianelle, D. Zuliani, D. Lucchesi and S. Montangero, npj Quantum Inf. 7 111 (2021) (28 Apr 2020) [36 citations].
• A meta-algorithm for classification using random recursive tree ensembles: A high energy physics application, V. Lalchand and A. Faul, arXiv 2001.06880 (19 Jan 2020). Thesis, Uses ATLAS Open Data
• End-to-end particle and event identification at the Large Hadron Collider with CMS Open Data, J. Alison, S. An, P. Bryant, B. Burkle, S. Gleyzer, M. Narain, M. Paulini, B. Poczos and E. Usai, arXiv 1910.07029 (15 Oct 2019) [4 citations].
• Interaction networks for the identification of boosted H \rightarrow b\overline{b} decays, E. Moreno, T. Nguyen, J. Vlimant, O. Cerri, H. Newman, A. Periwal, M. Spiropulu, J. Duarte and M. Pierini, Phys.Rev.D 102 012010 (2020) (26 Sep 2019) [74 citations]. Uses CMS Open Data
• Processing Columnar Collider Data with GPU-Accelerated Kernels, J. Pata and M. Spiropulu, arXiv 1906.06242 (14 Jun 2019) [2 citations]. Uses CMS Open Data
• End-to-end jet classification of quarks and gluons with the CMS Open Data, M. Andrews, J. Alison, S. An, P. Bryant, B. Burkle, S. Gleyzer, M. Narain, M. Paulini, B. Poczos and E. Usai, Nucl.Instrum.Meth.A 977 164304 (2020) (21 Feb 2019) [42 citations].
• Exploring End-to-end Deep Learning Applications for Event Classification at CMS, M. Andrews, M. Paulini, S. Gleyzer and B. Poczos, EPJ Web Conf. 214 06031 (2019) (01 Jan 2019) [7 citations].
• Machine Learning system mimicking student’s choice in Particle Data Analysis laboratory activity, V. Wachirapusitanand, N. Suwonjandee, B. Asavapibhop and N. Srimanobhas, J.Phys.Conf.Ser. 1144 012031 (2018) (17 Dec 2018).
• Fast and Accurate Simulation of Particle Detectors Using Generative Adversarial Networks, P. Musella and F. Pandolfi, Comput.Softw.Big Sci. 2 8 (2018) (02 May 2018) [87 citations].
• Expressing Parallelism with ROOT, D. Piparo, E. Tejedor, E. Guiraud, G. Ganis, P. Mato, L. Moneta, X. Valls Pla and P. Canal, J.Phys.Conf.Ser. 898 072022 (2017) (22 Nov 2017) [3 citations].
• Towards automation of data quality system for CERN CMS experiment, M. Borisyak, F. Ratnikov, D. Derkach and A. Ustyuzhanin, J.Phys.Conf.Ser. 898 092041 (2017) (25 Sep 2017) [12 citations].
• Application of a Convolutional Neural Network for image classification for the analysis of collisions in High Energy Physics, C. Madrazo, I. Cacha, L. Iglesias and J. de Lucas, EPJ Web Conf. 214 06017 (2019) (23 Aug 2017) [15 citations].
• Data Citation Services in the High-Energy Physics Community, P. Herterich and S. Dallmeier-Tiessen, D-Lib Magazine 22 (2016) (16 Jan 2016) [1 citation].
• The Higgs Machine Learning Challenge, C. Adam-Bourdarios, G. Cowan, C. Germain-Renaud, I. Guyon, B. Kégl and D. Rousseau, J.Phys.Conf.Ser. 664 072015 (2015) (23 Dec 2015) [22 citations].

General publications about Open Data

• Hybrid analysis pipelines in the REANA reproducible analysis platform, D. Rodríguez, R. Mačiulaitis, J. Okraska and T. Šimko, EPJ Web Conf. 245 06041 (2020) (01 Jan 2020) [1 citation].
• Open data provenance and reproducibility: a case study from publishing CMS open data, T. Šimko et. al., EPJ Web Conf. 245 08014 (2020) (01 Jan 2020) [1 citation].
• Using CMS Open Data for education, outreach and software development, Wunsch, Stefan, EPJ Web Conf. 245 08006 (2020) (01 Jan 2020).
• Open Data at CMS: Status and Plans, Mccauley, Thomas, PoS LHCP2019 260 (2019) (19 Sep 2019) [5 citations].
• Opportunities and challenges of Standard Model production cross section measurements in proton-proton collisions at \sqrt {s} =8 TeV using CMS Open Data, A. Apyan, W. Cuozzo, M. Klute, Y. Saito, M. Schott and B. Sintayehu, JINST 15 P01009 (2020) (18 Jul 2019) [15 citations].
• On the model dependence of fiducial cross-section measurements, G. Facini, K. Merkotan, M. Schott and A. Sydorenko, Mod.Phys.Lett.A 34 2050065 (2019) (04 Jun 2019) [3 citations].
• Open data as seen by the 4 LHC experiments, Lloret Iglesias, Lara, PoS LHCP2018 300 (2018) (21 Dec 2018).
• Open is not enough, X. Chen et. al., Nature Phys. 15 (2019) (15 Nov 2018) [24 citations].
• Strategic Plan for a Scientific Software Innovation Institute (S2I2) for High Energy Physics, P. Elmer, M. Neubauer and M. Sokoloff, arXiv 1712.06592 (18 Dec 2017) [13 citations].
• HEP data for everyone: CERN open data and the ATLAS and CMS experiments, McCauley, Thomas, PoS ICHEP2016 335 (2016) (22 Dec 2016) [2 citations].
• Visualization stabilization methods for the CERN ALICE high energy physics experiment, J. Myrcha and P. Rokita, Proc.SPIE Int.Soc.Opt.Eng. 10031 100313T (2016) (28 Sep 2016).
• ATLAS and CMS Data Release & Tools, Socher, Felix, PoS LHCP2016 112 (2016) (23 Sep 2016) [1 citation].
• Open Data and Data Analysis Preservation Services for LHC Experiments, J. Cowton, S. Dallmeier-Tiessen, P. Fokianos, L. Rueda, P. Herterich, J. Kunčar, T. Šimko and T. Smith, J.Phys.Conf.Ser. 664 032030 (2015) (23 Dec 2015) [9 citations].
• Open access to high-level data and analysis tools in the CMS experiment at the LHC, A. Calderon, D. Colling, A. Huffman, K. Lassila-Perini, T. McCauley, A. Rao, A. Rodriguez-Marrero and E. Sexton-Kennedy, J.Phys.Conf.Ser. 664 032027 (2015) (23 Dec 2015) [2 citations].